Perceptual blur and ringing metrics: application to JPEG2000

Abstract

We present a full-and no-reference blur metric as well as a full-reference ringing metric. These metrics are based on an analysis of the edges and adjacent regions in an image and have very low computational complexity. As blur and ringing are typical artifacts of wavelet compression, the metrics are then applied to JPEG2000 coded images. Their perceptual significance is corroborated through a number of subjective experiments. The results show that the proposed metrics perform well over a wide range of image content and distortion levels. Potential applications include source coding optimization and network resource management.

A Survey on Efficient No-Reference Blur Estimation Methods

“…This is a perceptual method [7] of blur estimation. The images are considered for evaluation by expert viewers.…”

Evaluation of image quality metrics for sharpness enhancement

“…2) No reference metrics: Recent NR metrics are based on the assumption that the distortion types are known (such as blocking artifacts [28], blur and noise [29], [30], [31], JPEG [32] or JPEG2000 compression [33], [34], and others [35], [36]). There is an important notion proposed by Ferzli and Karam: Just-Noticeable Blur (JNB) [37], [38], which takes into account the response of the HVS to sharpness at different contrast levels.…”

Multiscale anisotropic diffusion for ringing artifact suppression in geophysical deconvolution data

“…LL 2 represents the output from the low-pass filter in the horizontal and vertical directions, whereas HL i are Fig. 1 a Ringing artifacts in a compressed image (Marziliano and Dufaux 2004). b Ringing artifacts produced during deconvolution of geophysical data (Zuo et al 2009) the outputs from the high-pass filter in the vertical and horizontal directions.…”